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The Value of Lifetime Value

Most catalogers have used the term “customer lifetime value” (LTV), but few have actually calculated it, let alone used it in determining their marketing strategy. And that’s a shame. Without calculating LTV, it can be difficult to ascertain if your marketing program is going in the right direction, much less determine how to improve sales, get more revenue out of your current customers, and hone your circulation strategy to improve profitability.

Getting started

Lifetime value tracks the buying behavior of a group of customers and projects it into the future. Generally LTV is defined as the profits that you will receive from a given group of customers within the next three or four years.

In our example, let’s take customers who were acquired in 2000 and measure their behavior in that year, 2001, and 2002. To do so, we need to know:

the number of customers acquired in Year 1

the number of catalogs used to acquire these customers

the number of catalogs mailed to them after their first purchase

the average in-the-mail cost of the catalogs

the customer retention rate (Year 1 customers who continued to shop in subsequent years)

the customer referral rate (provided by Year 1 customers then and later)

the average order size each year

the average number of orders a year

the cost of goods sold

the average rate of returns

the revenue from and costs of shipping and handling

the market rate of interest

With these 12 factors, you can compile on an Excel spreadsheet what a typical cataloger lifetime value table looks like. (See the chart “Typical Cataloger Lifetime Value” at right. For the purposes of our example, we’ll leave out the data concerning returns, shipping and handling revenue and costs, and referrals.)

As you can see from the top line, only about one-third of the customers acquired in Year 1 came back to shop in Year 2. (This figure was approximately the same in all the market segments that we studied.) In Year 2 and subsequent years, the retention rate became much higher: More than 60% of those who did return in Year 2 were still buying in Year 3. And not only were they still buying, but their average order size went up, as did the number of orders per year. Finally, the profit per customer rose as well. You can see loyalty developing right before your eyes!

It took 800,000 catalogs to acquire the 200,000 Year 1 customers. Thereafter, to maintain sales the cataloger had to mail about eight catalogs per person per year.

The lifetime computation includes the discount rate. This simple calculation enables you to compute the net present value (NPV) of profits that you will receive in the future. The formula is discount = [1+ (i × 2)]n, where i = the market rate of interest, and n = the number of years since the customer was acquired. In our example, the market rate of interest is 6%:

0.06 × 2 = 0.12

1 + 0.12 = 1.12

In Year 2, then, the discount rate is 1.12. In Year 3, two years after the customer was acquired, the discount rate is 1.25 (1.122, or 1.12 × 1.12).

On the last line, the lifetime value is calculated by dividing the cumulative net present value of the profits in each year by the original number of Year 1 customers (200,000).

By itself, the figure $95.36 — the LTV in Year 3 — does not tell you much. What makes this number useful is to compare it to the same number derived from customers in various database segments. Using this LTV as a baseline, you can measure the value of peak-season buyers compared with buyers the rest of the year; sale-item buyers vs. regular-price buyers; Web buyers, phone buyers, retail buyers, and multichannel buyers; and buyers referred by other customers, among other options.

Get thee a database

To get the most out of LTV, you need a database that contains transactions and promotion history from all your channels. Sitting on top of the database you need an analytical tool such as Ensemble or Brio, so that you can get fast access to the data you need.

With a marketing database plus LTV analysis, you will have the tools in hand to learn a great deal more about your customers and to make profitable strategic decisions. Without a database, for example, a cataloger may look at the sale items in the catalog and say, “Yes, we sold a lot of those, but the sale cut into our margin. Was it worth it?” With a database, the cataloger could say, “These 20% of customers provide us with 80% of our revenue. What are they buying? Do they buy sale items? How can we reorganize our catalog and Web offerings to appeal to and retain them?”

The more data you have, the more questions you can answer. And the more questions you can answer, the more solutions and improvements you’ll be able to implement.

LTV in Action: Sears Canada

When general merchandiser Sears Canada built its first database combining retail and catalog customers, it learned that the average catalog customer spent $492 a year, while the average retail customer spent $1,102 a year. Most surprising, shoppers who used both channels were spending $1,883 a year.

This finding led Sears Canada to reorganize its corporate management and the layouts in 130 stores. The company put the catalog desk in the most traveled entrance to each store and provided catalog phones on the wall of every department with laminated catalog pages to help customers find what they wanted in the book if they could not find the item in the store. This shift alone led to increased sales of more than $250 million in the first year. — AMH

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